Gemini Omni 1.2 Flash Refine API

 1# pip install "segmind>=1.1.0"
 2# export SEGMIND_API_KEY="YOUR_API_KEY"
 3from segmind import SegmindClient, InferenceFailed, InferenceTimeout
 4
 5# Async (v2) — recommended for long-running / video models.
 6# run() blocks up to 600s; submit_async + job.wait(timeout=...) sets a longer
 7# deadline and keeps the request_id so you can re-poll later.
 8client = SegmindClient()                      # reads SEGMIND_API_KEY
 9payload = {
10    "previous_interaction_id": "",
11    "prompt": "Keep the same flat 2D vector motion-graphics infographic: deep teal background, bold white sans-serif type, locked-off camera, and the exact bar layout and grid. Change only two things - recolour the three bars from blue to warm amber, and rewrite the top title bar to read 'CITY SUNSHINE'. Every word spelled exactly as given, no other text. Add a soft chime the moment the title changes. Do not move the camera, the background grid, the labels or the bars.",
12}
13job = client.submit_async("gemini-omni-1.2-flash-refine", **payload)
14print(job.request_id)                         # available immediately
15try:
16    result = job.wait(timeout=900, interval=2.0)
17    print(result["status"])                  # COMPLETED
18    print(result.get("output"))              # model output (e.g. video URL)
19except InferenceTimeout as e:
20    print("still running:", e.request_id)    # re-poll later with this id
21except InferenceFailed as e:
22    print("failed:", e.detail)
23
24# Fast models (<=600s) can use the one-liner instead:
25# result = segmind.run("gemini-omni-1.2-flash-refine", **payload)